Job Summary
Proven AI-Native Experience: Deep, hands-on experience building software using advanced LLMs and AI coding assistants (e.g., Claude Code, GitHub Copilot, Cursor) and establishing LLM-based knowledge repositories (e.g., LLM Wiki).
Advanced Methodological Expertise: Extensive practical experience with the BMAD method and a strong grasp of comparable AI-assisted reasoning and development frameworks, including:
Agentic Frameworks: Structuring workflows using ReAct (Reasoning and Acting), Plan-and-Solve, or DSPy to ensure deterministic and reliable code generation.
Prompt Engineering Strategies: Mastery of Chain-of-Thought (CoT) and Tree-of-Thoughts (ToT) to guide LLMs through complex enterprise logic.
Architecture & Retrieval: Experience designing and implementing robust Retrieval-Augmented Generation (RAG) pipelines for internal tooling.
Enterprise Pragmatism: The ability to look past the hype of new tools and judge what is actually required to build secure, working enterprise software.
Mentorship & Process Design: A track record of setting up developer environments, standardizing workflows, and collaborating closely with cross-functional leadership to ensure long-term project sustainability.
Strategic Vision: Strong architectural instincts with the ability to build quickly for today while establishing a stable technological foundation for tomorrow's scale.
Act as the decision-maker on our initial AI development stack. Evaluate, select, and integrate cutting-edge tools (such as Claude Code and LLM Wiki) while applying the BMAD method, ensuring they meet enterprise requirements for security, scalability, and performance.
Key Responsibilities
Proven AI-Native Experience: Deep, hands-on experience building software using advanced LLMs and AI coding assistants (e.g., Claude Code, GitHub Copilot, Cursor) and establishing LLM-based knowledge repositories (e.g., LLM Wiki).
Advanced Methodological Expertise: Extensive practical experience with the BMAD method and a strong grasp of comparable AI-assisted reasoning and development frameworks, including:
Agentic Frameworks: Structuring workflows using ReAct (Reasoning and Acting), Plan-and-Solve, or DSPy to ensure deterministic and reliable code generation.
Prompt Engineering Strategies: Mastery of Chain-of-Thought (CoT) and Tree-of-Thoughts (ToT) to guide LLMs through complex enterprise logic.
Architecture & Retrieval: Experience designing and implementing robust Retrieval-Augmented Generation (RAG) pipelines for internal tooling.
Enterprise Pragmatism: The ability to look past the hype of new tools and judge what is actually required to build secure, working enterprise software.
Mentorship & Process Design: A track record of setting up developer environments, standardizing workflows, and collaborating closely with cross-functional leadership to ensure long-term project sustainability.
Strategic Vision: Strong architectural instincts with the ability to build quickly for today while establishing a stable technological foundation for tomorrow's scale.
Act as the decision-maker on our initial AI development stack. Evaluate, select, and integrate cutting-edge tools (such as Claude Code and LLM Wiki) while applying the BMAD method, ensuring they meet enterprise requirements for security, scalability, and performance.